br Molecular modeling study Molecular modeling study was ess
Molecular modeling study Molecular modeling study was essentially needed to understand and interpret the DHFR inhibitory pattern of this new class of compounds. Computational docking is an algorithm designed to estimate two main terms. The first is to determine the suitable position and the orientation of certain compounds pose inside the binding site in comparison to that of the X-ray crystallographic enzyme-substrate complex. The second term is the calculation of protein ligand interaction energy which is known as docking score. In the current study, C-Docker protocol was used for calculating the energy of protein, ligands alone and protein ligand complex using CHARMm forcefield. Validation of docking algorithm was achieved by re-docking MTX into the active site of hDHFR. This was found to retrieve the reported X-ray crystal structure binding mode of MTX, with root mean square difference (RMSD) between the top docking pose and original crystallographic geometry of 1.391Å , , , . Compounds 22 and 26 proved to be the most active members (IC50, 0.1 and 0.06μM, respectively) compared to the used positive control MTX (IC50, 0.08μM). It was interesting to start a comparative modeling study of the most active 26 and the least active 25 against MTX. The results of the lowest energy-minimized structures of 25 and 26 were used in the subsequent modeling experiments (Fig. 2a–c). The tertiary complex of human dihydrofolate reductase (hDHFR) crystal structure (pdb ID: 1U70 obtained from the protein data bank) and MTX were used as reference for modeling and docking . The binding of MTX to hDHFR is considered to be a complex interaction where hDHFR undergo isomerization and conformational changes leading to the tight binding with ionic bonding of N1 and 2-NH2 functions to Glu30. MTX binds also to DHFR through Asn64, Lys68, Arg28, Arg70, Val 115 and Ile7 amino GKT137831 molecular residues. The most active compound 26 and the least active 25 were docked into the hDHFR binding site as an attempt to explain their different destabilizing activity against DHFR assembly (Fig. 3a and b). Conformational analysis has been performed using the CHARMm force-field 3.4 (calculations in vacuum, bond dipole option for electrostatics, Polake Ribiere algorithm, and RMSD gradient of 0.01kcal/mol) implemented in Accelrys Discovery Studio Client 2.5 , , . The amino acids Phe 31 and Arg 22 are not one of the key residues involved in the recognition of the parent ligand MTX but they play a critical role in the binding of the most active compound 26. The 2D binding mode of 26 (IC50, 0.06μM) docked and minimized in the hDHFR binding pocket was shown in Fig. 4a–c. Compound 26 showed high affinity binding energy value of 46.65Kcal/mol toward Phe 31 residue which is linked to the thiazolo[4,5-d]pyridazine ring while Arg 22 residue is linked to 7-Phenyl moiety which suggest a similar interaction with the other active compound 22 in addition to a network of π-π interaction and hydrogen bonding. This pattern of binding explains the diminished activity of compound 25 (binding energy 20Kcal/mol), which lack any binding with those amino acids. According to the docking study results, the difference in biological activity of the tested compounds despite of their similar chemical structure could be explained. For the active molecules like 26, the presence of aromatic substituent with its conformational freedom seems to be crucial for the interaction, in addition to the presence of electron withdrawing group which favor MTX spatial arrangements. The inactive molecules like 25 were much more constrained and possibly having different structural attributes related to the aromatic ring. Ligand-based active site alignment study by docking inside the binding pocket is a well-known technique for structural analysis of ligand complexes . In the present, study flexible alignment comparative modeling experiment was performed (Fig. 5). An alignment is considered to be successful when the molecule strain energy is small, possessing similar shapes and their aromatic atoms overlap to show the similarity between the 3D structures of the most active compound 26 and MTX. Initial approach was applied to employ CharmM /MMFF94 flexible alignment automatically generated superposition with minimal user bias.